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import yaml
from utils import set_type, set_operator_role_and_location, set_eu_market_status, check_within_scope
# Create some variables we will use throughout our analysis
project_variables = {
"ai_project_type": {
"ai_system": False,
"gpai_model": False,
"high_risk_ai_system": False,
"gpai_model_systematic_risk": False
},
"operator_role": {
"provider": False,
"deployer": False,
"importer": False,
"distributor": False,
"product_manufacturer": False,
"eu_located": False
},
"eu_market_status": {
"placed_on_market": False,
"put_into_service": False,
"output_used": False
}
}
def run_compliance_analysis_on_project(project_cc_yaml):
# Determine project type (AI system vs. GPAI model) as well as operator type. We will use these for different things.
project_type = set_type(project_variables, project_cc_yaml)
set_operator_role_and_location(project_variables, project_cc_yaml)
set_eu_market_status(project_variables, project_cc_yaml)
# Check if the project is within scope of the Act. If it's not, the analysis is over.
if check_within_scope(project_cc_yaml):
msg = ("Project is within the scope of Act. Let's continue...")
else:
msg = ("Project is not within the scope of what is regulated by the Act.")
# # Check for prohibited practices. If any exist, the analysis is over.
# if check_prohibited(project_cc_yaml) == True:
# print("Project contains prohibited practices and is therefore non-compliant.")
# msg = ("Project is non-compliant due to a prohibited practice.")
# else:
# print("Project does not contain prohibited practies. Let's continue...")
# If project is high-risk AI system, check that is has met all the requirements for such systems:
if project_type == "high_risk_ai_system":
# Do this by examining the Project CC
for key, value in project_cc_yaml['risk_management_system']:
if not value:
msg = ("Because of project-level characteristics, this high-risk AI system fails the risk management requirements under Article 9.")
for key, value in project_cc_yaml['technical_documentation']:
if not value:
msg = ("Because of project-level characteristics, this high-risk AI system fails the risk management requirements under Article 11.")
for key, value in project_cc_yaml['record_keeping']:
if not value:
msg = ("Because of project-level characteristics, this high-risk AI system fails the risk management requirements under Article 12.")
for key, value in project_cc_yaml['transparency_and_provision_of_information_to_deployers']:
if not value:
msg = ("Because of project-level characteristics, this high-risk AI system fails the transparency requirements under Article 13.")
for key, value in project_cc_yaml['human_oversight']:
if not value:
msg = ("Because of project-level characteristics, this high-risk AI system fails the human oversight requirements under Article 14.")
for key, value in project_cc_yaml['accuracy_robustness_cybersecurity']:
if not value:
msg = ("Because of project-level characteristics, this high-risk AI system fails the accuracy, robustness, and cybersecurity requirements under Article 15.")
for key, value in project_cc_yaml['quality_management_system']:
if not value:
msg = ("Because of project-level characteristics, this high-risk AI system fails the accuracy, robustness, and cybersecurity requirements under Article 17.")
return msg
def run_compliance_analysis_on_data(data_cc_yaml):
for key, value in data_cc_yaml['data_and_data_governance']:
if not value:
msg = (f"Because of the dataset represented by , this high-risk AI system fails the data and data governance requirements under Article 10.")
for key, value in data_cc_yaml['technical_documentation']:
if not value:
msg = (f"Because of the dataset represented by , this high-risk AI system fails the technical documentation requirements under Article 11.")
for key, value in data_cc_yaml['transparency_and_provision_of_information_to_deployers']:
if not value:
msg = (f"Because of the dataset represented by , this high-risk AI system fails the transparency requirements under Article 13.")
for key, value in data_cc_yaml['quality_management_system']:
if not value:
msg = (f"Because of the dataset represented by , this high-risk AI system fails the quality management requirements under Article 17.")
return msg
def run_compliance_analysis_on_model(model_cc_yaml):
for key, value in model_cc_yaml['risk_management_system']:
if not value:
msg = (f"Because of the model represented by , this high-risk AI system fails the risk management requirements under Article 9.")
for key, value in data_cc_yaml['technical_documentation']:
if not value:
msg = (f"Because of the model represented by , this high-risk AI system fails the technical documentation requirements under Article 11.")
for key, value in data_cc_yaml['transparency_and_provision_of_information_to_deployers']:
if not value:
msg = (f"Because of the model represented by , this high-risk AI system fails the transparency requirements under Article 13.")
for key, value in data_cc_yaml['accuracy_robustness_cybersecurity']:
if not value:
msg = (f"Because of the model represented by , this high-risk AI system fails the quality management requirements under Article 15.")
for key, value in data_cc_yaml['quality_management_system']:
if not value:
msg = (f"Because of the model represented by , this high-risk AI system fails the quality management requirements under Article 17.")
return msg
# # If the project is a GPAI model, check that is has met all the requirements for such systems:
# if gpai_model:
# # Do this by examining the Project CC
# for key, value in project_cc_yaml['gpai_model_provider_obligations']:
# if not value:
# msg = ("GPAI model fails the transparency requirements under Article 53.")
# # Do this by examining any and all Data CCs too
# for filename in os.listdir(folder_path):
# # Check if the search word is in the filename
# if "data_cc.md" in filename.lower():
# # If it is, load the yaml
# with open(folder_path + filename, 'r') as file:
# data_cc_yaml = yaml.safe_load(file)
# for key, value in data_cc_yaml['gpai_requirements']['gpai_requirements']:
# if not value:
# msg = (f"Because of the dataset represented by {filename}, this GPAI fails the transparency requirements under Article 53.")
# # Do this by examining any and all Model CCs too
# for filename in os.listdir(folder_path):
# # Check if the search word is in the filename
# if "model_cc.md" in filename.lower():
# # If it is, load the yaml
# with open(folder_path + filename, 'r') as file:
# model_cc_yaml = yaml.safe_load(file)
# for key, value in model_cc_yaml['obligations_for_providers_of_gpai_models']:
# if not value:
# msg = (f"Because of the model represented by {filename}, this GPAI fails the transparency requirements under Article 53.")
# # If the project is a GPAI model with systematic risk, check that is has additionally met all the requirements for such systems:
# if gpai_model_systematic_risk:
# # Do this by examining the Project CC
# for key, value in project_cc_yaml['gpai_obligations_for_systemic_risk_models']:
# if not value:
# msg = ("GPAI model with systematic risk fails the transparency requirements under Article 55.")
# # Do this by examining any and all Model CCs too
# for filename in os.listdir(folder_path):
# # Check if the search word is in the filename
# if "model_cc.md" in filename.lower():
# # If it is, load the yaml
# with open(folder_path + filename, 'r') as file:
# model_cc_yaml = yaml.safe_load(file)
# for key, value in model_cc_yaml['obligations_for_providers_of_gpai_models_with_systemic_risk']:
# if not value:
# msg = (f"Because of the model represented by {filename}, this GPAI model with systematic risk fails the transparency requirements under Article 55.")
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